A Spine Loading Model of Women in the Military

Abstract

The risk of low-back disorders (LBD) may be particularly great for women in the military, influencing training, costs and military readiness. The goal of this research is to quantify musculoskeletal loads on the spine of women performing manual materials handling tasks. This will permit assessment of risk factors for military women, and the potential to evaluate tasks and training methods for female military personnel. This goal of this research was accomplished by quantifying trunk geometry via MRI and incorporating muscle fiber orientation, investigating the muscle length-strength and force-velocity relationships during lifting trials, and developing and validating the female biomechanical model utilizing these findings as inputs. Females exhibited smaller muscle physiological cross-sectional areas, moment-arms, and different characteristics for the length-strength and force-velocity modulation factors. Thus, biomechanical torso models need gender specific inputs for predicting spinal loading. Evaluation of spinal loading for a simulated military manual materials handling task indicated that females and males experienced similar magnitudes of spinal loading (e.g., compression force and shear forces) for many of the same tasks. However, since females tend to exhibit lower intervertebral disc compression force tolerance than males, they may be at an elevated risk for low back injury when performing the same tasks.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2000
Accession Number
ADB261561

Entities

People

  • William S. Marras

Organizations

  • Ohio State University

Tags

Communities of Interest

  • Air Platforms
  • Biomedical

DTIC Thesaurus Topics

  • Army Personnel
  • Back Injuries
  • Computers
  • Data Analysis
  • Data Science
  • Data Sets
  • Databases
  • Descriptive Analytics
  • Experimental Design
  • Health Services
  • Information Science
  • Knowledge Management
  • Medical Personnel
  • Pain
  • Spine
  • Statistical Analysis
  • Three Dimensional

Readers

  • Computational Modeling and Simulation
  • Exercise and Sports Science.
  • Logistics and Supply Chain Management.